Fluorescence lifetime imaging signatures for early diagnosis of lung cancer, and its regulation through the adenosine pathway.
Lead Research Organisation:
University of Edinburgh
Department Name: Centre for Inflammation Research
Abstract
Lung cancer is the leading cause of cancer related deaths worldwide. Unfortunately, current methods like CT scans have limitations in detecting lung cancer early and evaluating treatment response promptly, causing delays in diagnosis/therapy. To address this, I will investigate the potential of a technology called fluorescent lifetime imaging (FLIM). FLIM can detect emitted light from cells in the body, and I have shown that the light emitted from cells within a cancer differs from that of non-cancerous cells. Although the reason for this discrepancy is unknown, my findings suggest a correlation with how cells regulate their metabolism, through a chemical called adenosine. The FLIM technology is state-of-the-art and designed for use during bronchoscopy (where a camera is inserted into the lungs to examine suspected cancers). Here, using specialised fibres that can reach lesions/tumours we can obtain real-time metabolic profiles of the cancerous tissue, enabling immediate cancer diagnosis. I will also use small chemical compounds that detect the overactivity of two cell types crucial in the response to treatments: fibroblasts and T cells. This approach may provide early indications of treatment effectiveness, such as chemotherapy, before changes are visible on CT scans.
Aims:
1) Define FLIM signals in lung cancer at both the cellular and whole cancer levels.
2) To investigate the relationship between FLIM signals and the activity of the adenosine pathway in lung cancer, linked to drug treatments.
Objectives:
Objective 1. Determine the cell specific FLIM signal in lung cancer and relate this to both the cells level of activation and function.
Using surgically resected cancers, I will breakdown these into their individual cell component and measure the cell specific FLIM signal in each cell type. Parallel confirmatory experiments will tell us the cell activation and function levels. Then, using advanced culture methods that mimic cancer conditions I will understand what changes occur with drug treatments as we would use in the clinic, and relate this to how efficiently the cancer cells are killed. Finally, using an established large pathology set of lung cancers, I will make a unique atlas of all the cell types in cancer and their FLIM signal. This will be made into a shared community resource for other researchers.
Objective 2. I will use a small device to allow us to understand how multiple combinations of drugs work in lung cancer, linked to FLIM.
Using a device capable of delivering 20 drug combinations to small, confined areas of the cancer (less than 1 mm distance), I will study multiple combinations of drugs that target the adenosine pathway in lung cancer patients who have had their cancer removed. Using multiple laboratory techniques, including FLIM, I will measure how well the drug combinations have performed. The optimal combinations will be delivered (without the device) to patients a few days before their surgery for confirmation. Ultimately, we will aim to do the whole device experiments in patients' cancers before surgery, but this will be done with further research funding and on completion of the above stages of research.
Objective 3. Assess FLIM signals in patients and combine this with small chemical compounds that report activity of fibroblasts and T cells.
I will use an existing trial infrastructure in Edinburgh and will recruit patients with i) suspected cancer, ii) undergoing surgery, iii) planned for drug-based cancer treatment. Each group will have FLIM imaging combined with the chemical probes that can identify activated fibroblasts and signatures of cell death caused by T cells. This will gain valuable insights into the behaviour of the cancer and its response to therapy by FLIM.
Together, this will determine if FLIM can be used as a tool for immediate diagnosis and early assessment of treatment response in lung cancer, ultimately enhancing outcomes for patients.
Aims:
1) Define FLIM signals in lung cancer at both the cellular and whole cancer levels.
2) To investigate the relationship between FLIM signals and the activity of the adenosine pathway in lung cancer, linked to drug treatments.
Objectives:
Objective 1. Determine the cell specific FLIM signal in lung cancer and relate this to both the cells level of activation and function.
Using surgically resected cancers, I will breakdown these into their individual cell component and measure the cell specific FLIM signal in each cell type. Parallel confirmatory experiments will tell us the cell activation and function levels. Then, using advanced culture methods that mimic cancer conditions I will understand what changes occur with drug treatments as we would use in the clinic, and relate this to how efficiently the cancer cells are killed. Finally, using an established large pathology set of lung cancers, I will make a unique atlas of all the cell types in cancer and their FLIM signal. This will be made into a shared community resource for other researchers.
Objective 2. I will use a small device to allow us to understand how multiple combinations of drugs work in lung cancer, linked to FLIM.
Using a device capable of delivering 20 drug combinations to small, confined areas of the cancer (less than 1 mm distance), I will study multiple combinations of drugs that target the adenosine pathway in lung cancer patients who have had their cancer removed. Using multiple laboratory techniques, including FLIM, I will measure how well the drug combinations have performed. The optimal combinations will be delivered (without the device) to patients a few days before their surgery for confirmation. Ultimately, we will aim to do the whole device experiments in patients' cancers before surgery, but this will be done with further research funding and on completion of the above stages of research.
Objective 3. Assess FLIM signals in patients and combine this with small chemical compounds that report activity of fibroblasts and T cells.
I will use an existing trial infrastructure in Edinburgh and will recruit patients with i) suspected cancer, ii) undergoing surgery, iii) planned for drug-based cancer treatment. Each group will have FLIM imaging combined with the chemical probes that can identify activated fibroblasts and signatures of cell death caused by T cells. This will gain valuable insights into the behaviour of the cancer and its response to therapy by FLIM.
Together, this will determine if FLIM can be used as a tool for immediate diagnosis and early assessment of treatment response in lung cancer, ultimately enhancing outcomes for patients.
